Load data

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Load functions and groups

# Functions: 
source(paste0(WD, "scripts/finding_the_core.R"))
source(paste0(WD, "../2023_RETHINK_sample_collection/scripts/functions/PCOA_from_long_data.R"))
source(paste0(WD, "../2023_MiDAS_OK_testing/script/ADONIS_from_long_data.R"))
# Make PCoA on the differnet taxonomic levels 
source(paste0(WD, "../2023_RETHINK_sample_collection/scripts/functions/PCOA_from_long_data.R"))
source(paste0(WD, "scripts/functions/growing_dying_bar_plot.R"))


SampleContent2_colors <- c("#1e8449","#21618C","#b03a2e", "#ffb74d", "#e65100", "#795548")


# Functional groups
Nitrifiers = c("g__Nitrosomonas","g__Nitrosospira","g__Nitrospira","g__Nitrotoga")
Denitrifiers = c("g__Zoogloea", "g__Rhodoferax", "g__Thauera", "g__Rhodobacter", 
                 "g__Sulfuritalea", "g__Paracoccus", "g__Azoarcus")
PAOs <- c(
 "g__Ca_Phosphoribacter",
 "g__Azonexus",
 "g__Ca_Accumulibacter",
 "g__Ca_Lutibacillus",
 "g__Tetrasphaera",
 "g__Microlunatus" )
GAOs <- c("g__Ca_Competibacter",
              "g__Defluviicoccus",
              "g__Propionivibrio",
              "g__Micropruina",
              "g__Ca_Contendobacter",
              "g__Ca_Proximibacter")
Filaments <- c("g__Ca_Microthrix", "g__Leptothrix","g__Sphaerotilus","g__Ca_Villigracilis","g__Trichococcus",
               "g__Thiothrix","g__Ca_Promineofilum","Haliscomenobacter","g__Gordonia","g__Sarcinithrix",
               "g__Ca_Amarolinea","g__Kouleothrix","g__Ca_Alysiosphaera",
               "g__Nocardioides","g__midas_g_1668","g__Anaerolinea","g__Ca_Caldilinea",
               "g__Ca_Hadersleviella","g__midas_g_344",
               "g__Skermania","g__Ca_Nostocoida","g__Neomegalonema","g__Beggiatoa",
               "g__Ca_Brevefilum") 



df_functional <- 
  tibble(Genus = c(Nitrifiers, Denitrifiers, PAOs, GAOs, Filaments), 
         functional_group =  c(rep("Nitrifiers", length(Nitrifiers)), 
                               rep("Denitrifiers", length(Denitrifiers)),
                               rep("PAOs", length(PAOs)),
                               rep("GAOs", length(GAOs)),
                               rep("Filaments", length(Filaments))
                               ))

Save ampvis data to Rodrigo

Ordinations of sewer envionements (genus level)

Biofilm only

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HM at the genus level: top 15 for each system

Figure XX: Most abundant genera across sewer envionments merged sample sites

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Figure XX: Most abundant genera across sewer envionments per sample site

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HM at the genus level: top 15 for each system –> also SWW

Figure XX: Most abundant genera across sewer envionments merged sample sites

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PAOs and GAOs in the sewer

Figure SXX: Heatmap of PAO and GAOs merged samplesites

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Figure SXX: Heatmap of PAO and GAOs for each samplesite

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Each site by date

Figure XX: Biofilm (g)

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Figure XX: Biofilm (p.)

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Figure XX: Biofilm (e.p.)

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Most abundant genera by date

NOT MADE YES

Figure XX: Biofilm (g)

Figure XX: Biofilm (p.)

Figure XX: Biofilm (e.p.)